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| 005 | 20260817163102.0 | ||
| 008 | 200911s2017 th a a m 000 eng d | ||
| 035 | _a.b12345507 | ||
| 099 | 9 | _aAIT RSPR no.CS-17-01 | |
| 100 | 1 | _aVyshnavi, Raja | |
| 245 | 1 | 0 | _aApplying data mining techniques on yelp challenge dataset |
| 260 |
_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2017 |
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| 300 |
_a1 online resource (63 p.) : _bill. |
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| 490 | 1 |
_aResearch studies project report ; _vno. CS-17-01 |
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| 500 | _aA research report submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science, School of Engineering and Technology | ||
| 502 | _aResearch Studies Project Report (M. Eng.) - Asian Institute of Technology, 2017 | ||
| 520 | _aMining techniques have proven to be effective in exploring data.In my research study I want to use Data mining Techniques on the Yelp Data set.Yelp is one of the best website for users to review the local business of different categories . Users write text reviews about the business and each business have different business categories. There is an Data set challenge given by Yelp to the students to use the data in a innovative way . The problem statement of my research study is to predict the business categories of the business based on the user review. The main idea here is to apply data mining algorithms like Nave Bayes, SVM, Logistic regression, ML-KNN on the yelp data set and predict the categories from the user reviews for these classifiers formed and calculate the accuracy of the classifiers. | ||
| 650 | 0 | _aData mining | |
| 650 | 0 | _aComputer algorithms | |
| 700 | 1 |
_aGuha, Sumanta, _eChairperson |
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| 700 | 1 |
_aPhan, Minh Dung, _eExamination Committee |
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| 700 | 0 |
_aChutiporn Anutariya, _eExamination Committee |
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| 710 | 2 |
_aAsian Institute of Technology Fellowship, _eScholarship Donor |
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| 810 | 2 |
_aAsian Institute of Technology. _tResearch studies project report ; _vno. CS-17-01 |
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| 856 |
_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B06996 |
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| 962 |
_a000:001:PDF:b1234550:004614:0:0:0:0:0:0 _tClick to view Abstract _vn |
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